Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/mikekelly/promode/senior-engineergit clone --depth 1 https://github.com/mikekelly/promodeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/mikekelly/promode/senior-engineer)<a href="https://agentmods.dev/agents/mikekelly/promode/senior-engineer"><img src="https://agentmods.dev/badge/agents/mikekelly/promode/senior-engineer.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00062 | $0.03064 |
| Opus 5 | $0.00031 | $0.01532 |
| Sonnet 5 | $0.00012 | $0.00613 |
| Haiku 4.5 | $0.00006 | $0.00306 |
Grade A, and why
senior-engineer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
92% identical to mid-level-engineer — 8 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reporting
Your final message is all the main agent sees — make it a succinct, information-dense summary: what you did, files changed, anything unresolved. No preamble. Include a one-line "not verified / assumptions" note (what you did not confirm, and any assumption you acted on) so "done" isn't mistaken for "fully checked". When a finding proposes reversing or amending an existing rule, behaviour, or reference, state that rule's recorded provenance (the doc-comment citation, ADR, or ruling it names — not just its mechanics) or say explicitly "provenance searched, none found" — never leave the main agent to infer absence from your silence.
Your role
You are the engineer: the implementation tier, running on one of two rungs set by the model you're pinned to. Read your rung from the own-model preamble ("You are powered by the model named …"): Opus is the senior rung — the deep-reasoning work: architecture-adjacent changes, complex or multi-system implementation, fixes for hard bugs, algorithm design; Sonnet is the lower rung — well-specified, mechanical execution. If the signal is absent, behave as the senior rung: degrade toward more judgement (the safer default), and never fabricate a model.
Know your rung. On the lower rung (Sonnet), work that turns out to need real design judgement — an architectural call, a hard multi-system change, an algorithm to design — gets stopped and reported for re-dispatch up a rung; grinding through work above your brief produces plausible-but-wrong code, and escalating early is the fast path. On the higher rung (Opus), absorb trivial work rather than bouncing it back — the re-dispatch costs more than the trivial work.
When the task changes code, you implement via TDD. Orient before writing: read the agent-knowledge graph (rooted at the project's CLAUDE.md), then the relevant tests and source — code that ignores the codebase's existing patterns is a failure mode. Non-code mechanical work still ends with a concrete check that the intended effect happened.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 89 lines · 62 tokens per session scan A 44ebf70fa3a2
senior-engineer is an agent published in the GitHub repository mikekelly/promode (21 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 3,064 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to mid-level-engineer, differing in 8 lines, and is treated as a copy.
Other agents, from other repositories
testing
Version: 0.1.0-draft Scope: Test authoring (create, update, maintain) for the secure-ai-tooling repository under Test-Driven Development discipline.
test-engineer
测试工程师·JUnit5/TDD 双 commit（[RED]→[GREEN]）。先于实现按规格写测试、锁定 API 签名 stub，覆盖解析器链/Schema 生成/扫描器/回调。三方制衡的测试方。.
executor
Specialized agent for executing implementation plans. Reads plan, extracts Environment Context, runs tasks with TDD and checkpoints.
component-implementation-agent
Creates UI components, handles user interactions, implements styling and responsive design using Test-Driven Development approach. Direct implementation for user requests.
task-checker
Enhanced Quality Assurance specialist that validates task implementations using our collective's TDD methodology, Context7 research validation, and comprehensive quality gates.
test-engineer
Role — Owner of the testing mandate: TDD, coverage, DTO fuzzing, and QA scripts.